Ant colony system algorithm for the optimization of beer fermentation control.

Jie Xiao, Ze-Kui Zhou, Guang-Xin Zhang
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引用次数: 20

Abstract

Beer fermentation is a dynamic process that must be guided along a temperature profile to obtain the desired results. Ant colony system algorithm was applied to optimize the kinetic model of this process. During a fixed period of fermentation time, a series of different temperature profiles of the mixture were constructed. An optimal one was chosen at last. Optimal temperature profile maximized the final ethanol production and minimized the byproducts concentration and spoilage risk. The satisfactory results obtained did not require much computation effort.

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蚁群算法在啤酒发酵控制中的应用。
啤酒发酵是一个动态的过程,必须沿着一定的温度曲线进行引导才能获得预期的结果。采用蚁群算法对该过程的动力学模型进行优化。在一段固定的发酵时间内,构建了一系列不同的混合物温度曲线。最后选出了最优方案。优化的温度分布使最终乙醇产量最大化,并使副产物浓度和腐败风险最小化。所得结果令人满意,计算量不大。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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